Abstract
As part of expert evidence, in proceedings on traffic accidents, the basic basis for the analysis of the accident scene is the scene of the traffic accident, where vehicles and other participants in the traffic accident leave various traces. For example, according to the extent and nature of damage to vehicles and injuries to road users, it is possible to determine the nature of the collision and the approximate impact speed of the vehicle. Traffic accident analysts (forensic experts) perform accident scene analysis, where they assess the origin and causes of traffic accidents, evaluate driving techniques, determine the possibilities of avoiding a traffic accident, etc. For the calculation of various movement quantities of the accident event (calculation models), they use various application, mathematical simulation programs to determine the origin and course of the accident event. The paper deals with the analysis of an accident event in the configuration of vehicle - motorcycle - pedestrian, which occurred in the urban area of the village, on a road with a high frequency of pedestrians. In addition to the graphical analysis of the course of the accident in the PC-Crash simulation program (version 13.1), the driver’s driving technique and pedestrian movement are evaluated. At the same time, the possibilities of averting traffic accidents on the part of individual road users are determined.
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Acknowledgements
This work was supported by the Slovak Research and Development Agency under contract no. APVV-20-0626. This work was created within the project APVV-20-0626: Biofidelic human body surrogate to increase the objectivity within the forensic analysis of road traffic accidents.
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Macurová, Ľ., Kohút, P., Kasanický, G., Ballay, M. (2023). Expert Evidence in the Analysis of the Accident Event – Vehicle, Motorcycle and Pedestrian. In: Prentkovskis, O., Yatskiv (Jackiva), I., Skačkauskas, P., Maruschak, P., Karpenko, M. (eds) TRANSBALTICA XIII: Transportation Science and Technology. TRANSBALTICA 2022. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-031-25863-3_39
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DOI: https://doi.org/10.1007/978-3-031-25863-3_39
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